Machine learning and radiomics for predicting efficacy of programmed cell death protein 1 inhibitor for small cell lung cancer: A multicenter cohort study

Pulin Li; Ling Huang; Rui Han; Min Tang; Guanghe Fei; Daxiong Zeng; Ran Wang

doi:10.1002/ctm2.1673

Clinical and Translational Medicine ›› 2024, Vol. 14 ›› Issue (6) : e1673 DOI: 10.1002/ctm2.1673

LETTER TO THE JOURNAL

Machine learning and radiomics for predicting efficacy of programmed cell death protein 1 inhibitor for small cell lung cancer: A multicenter cohort study

Pulin Li ¹
, Ling Huang ²
, Rui Han ¹
, Min Tang ¹
, Guanghe Fei ¹^,^†
, Daxiong Zeng ³^,^†
, Ran Wang ¹^,^†

Author information +

History +

PDF

Cite this article

Download citation ▾

Pulin Li, Ling Huang, Rui Han, Min Tang, Guanghe Fei, Daxiong Zeng, Ran Wang. Machine learning and radiomics for predicting efficacy of programmed cell death protein 1 inhibitor for small cell lung cancer: A multicenter cohort study. Clinical and Translational Medicine, 2024, 14(6): e1673 DOI:10.1002/ctm2.1673

登录浏览全文

4963

注册一个新账户忘记密码

References

Publishing order | Descend order by publishing year | Descend order by cited within

[1]	Bade BC, Dela Cruz CS. Lung cancer 2020: epidemiology, etiology, and prevention. Clin Chest Med. 2020;41(1):1-24.

[2]	van Meerbeeck JP, Fennell DA, De Ruysscher DK. Small-cell lung cancer. Lancet. 2011;378(9804):1741-1755.

[3]	Zugazagoitia J, Paz-Ares L. Extensive-stage small-cell lung cancer: first-line and second-line treatment options. J Clin Oncol. 2022;40(6):671-680.

[4]	Goetze TO. Immunotherapy: a new era in small-cell lung cancer. Lancet. 2019;394(10212):1884-1885.

[5]	Lee A. Serplulimab: first approval. Drugs. 2022;82(10):1137-1141.

[6]	Shao T, Zhao M, Liang L, Tang W. Serplulimab plus chemotherapy vs chemotherapy for treatment of US and Chinese patients with extensive-stage small-cell lung cancer: a cost-effectiveness analysis to inform drug pricing. BioDrugs. 2023;37(3):421-432.

[7]	Oncology Society of Chinese Medical Association. Guideline for clinical diagnosis and treatment of lung cancer (2023 edition). Chin J Oncol. 2023;45(1):1-30.

[8]	van Griethuysen JJM, Fedorov A, Parmar C, et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77(21):e104-e107.

[9]	Shaker B, Yu MS, Song JS, et al. LightBBB: computational prediction model of blood-brain-barrier penetration based on LightGBM. Bioinformatics. 2021;37(8):1135-1139.

[10]	Peng Y, Zhao S, Zeng Z, Hu X, Yin Z. LGBMDF: a cascade forest framework with LightGBM for predicting drug-target interactions. Front Microbiol. 2022;13:1092467.

RIGHTS & PERMISSIONS

2024 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics